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Relax! Flux is the ML library that doesn't make you tensor
Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equat…
Course 18.S191 at MIT, Fall 2022 - Introduction to computational thinking with Julia
Bayesian inference with probabilistic programming.
A general-purpose probabilistic programming system with programmable inference
Unicode-based scientific plotting for working in the terminal
A generic, simple and fast implementation of Deepmind's AlphaZero algorithm.
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
Forward Mode Automatic Differentiation for Julia
Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
A reinforcement learning package for Julia
Repository of best practices for deep learning in Julia, inspired by fastai
Julia Implementation of Transformer models
Dash for Julia - A Julia interface to the Dash ecosystem for creating analytic web applications in Julia. No JavaScript required.
Julia implementation of various rigid body dynamics and kinematics algorithms
Sensible extensions for exposing torch in Julia.
Neural Network primitives with multiple backends
Wrapping deep learning models from the package Flux.jl for use in the MLJ.jl toolbox